以时为步长的塔河林业局白桦林地表死可燃物含水率预测方法

doi:10.11707/j.1001-7488.20131216

Abstract

Abstract:

Accurately prediction of the dead fuel moisture content on the forest floor is very important for fire behavior forecast and fire danger rating estimation. Dynamics of hourly moisture content of the surface fine dead fuels under birch (Betula platyphylla) stand in Tahe Forestry Bureau, Daxing'anling Region, Heilongjiang Province, China was modeled using direct timelag methods with Nelson and Simard equilibrium moisture content models and a meteorological variable regression method. The mean absolute error of Nelson(1.01%~1.17%) and Simard(1.06%~1.39%)were lower than that of meteorological variable regression method(1.62%~3.01%), which indicated that hourly prediction of fuel moisture by the direct timelag methods would be applicable to the region.

Key words: birch, dead fuel on the forest floor, moisture content, prediction model

CLC Number:

S762

Yu Hongzhou, Jin Sen, Di Xueying. Models for Predicting the Hourly Fuel Moisture Content on the Forest Floor of Birch Stands in Tahe Forestry Bureau[J]. Scientia Silvae Sinicae, 2013, 49(12): 108-113.

References

陈鹏宇. 2011. 帽儿山林场地表死可燃物含水率直接估计法的误差分析. 哈尔滨: 东北林业大学硕士学位论文.
邸雪颖. 1993. 林火预测预报. 哈尔滨: 东北林业大学出版社.
傅泽强, 陈动, 王玉彬. 2001. 大兴安岭森林火灾与气象条件的相互关系. 东北林业大学学报, 29(1): 12-15.
何忠秋, 张成钢, 牛永杰. 1996. 森林可燃物湿度研究综述. 世界林业研究, (5): 26-30.
胡海清. 2005. 林火生态与管理. 北京: 中国林业出版社.
胡海清, 赵致奎, 王晓春, 等. 2010. 基于树轮火疤塔河蒙克山樟子松林火灾的频度分析. 生态学报, 30(23): 6372-6379.
胡海清, 魏书精, 孙龙. 2012. 大兴安岭2001—2010年森林火灾碳排放的计量估算. 生态学报, 32(17): 5373-5386.
胡远满, 徐崇刚, 常禹, 等. 2004. 空间直观景观模型LANDIS在大兴安岭呼中林区的应用. 生态学报, 24(9): 1846-1856.
金森, 李亮. 2010. 时滞和平衡含水率的直接估计法的有效性分析. 林业科学, 46(2): 95-102.
金森, 陈鹏宇. 2011a. 樟子松针叶床层结构对失水过程中含水率参数的影响. 林业科学, 47(4): 114-120.
金森, 李亮, 赵玉晶. 2011b. 用直接估计法预测落叶松枯枝含水率的稳定性和外推误差分析. 林业科学, 47(6): 114-121.
李晓娜, 贺红士, 吴志伟, 等. 2012. 大兴安岭北部森林景观对气候变化的响应. 应用生态学报, 23(12): 3227-3235.
刘志华, 常禹, 陈宏伟, 等. 2008. 大兴安岭呼中林区地表死可燃物载荷量空间格局. 应用生态学报, 19(3): 487-493.
刘曦, 金森. 2007. 平衡含水率法预测死可燃物含水率的研究进展. 林业科学, 43(12): 126-133.
邱扬, 李湛东, 张玉钧, 等. 2006. 火干扰对大兴安岭北部原始林下层植物多样性的影响. 生态学报, 26(9): 2863-2869.
舒展. 2011. 气候变化对大兴安岭塔河林业局森林火灾的影响研究. 哈尔滨: 东北林业大学博士学位论文.
王会研, 李亮, 金森, 等. 2008. 一种新的可燃物含水率预测方法介绍. 森林防火, 99(4): 11-12.
王文娟, 常禹, 刘志华, 等. 2009. 大兴安岭呼中林区地表死可燃物含水量及其环境梯度分析. 生态学杂志, 28(2): 209-215.
周以良. 1991. 中国大兴安岭植被. 北京: 科学出版社.
Anderson H E, Schuetle R D, Mutch R W. 1978. Timelag and equilibrium moisture content of ponderosa pine needles. Ogden, UT: Intermountain Forest and Range Experiment Station, Forest Service, United States Department of Agriculture.
Anderson H E. 1990. Predicting equilibrium moisture content of some foliar forest litter in the northern Rocky Mountains. USDA Forest Service Research Paper INT-429, Ogden, UT: Intermountain Forest and Range Experiment Station, Forest Service, United States Department of Agriculture.
Catchpole E A, Catchpole W R, Viney N R, et al. 2001. Estimating fuel response time and predicting fuel moisture content from field data. International Journal of Wildland Fire, 10: 215-222.
Chuvieco E, Aguado I, Dimitrakopoulos A P. 2004. Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment. Canadian Journal of Forest Research, 34: 2284-2293.
Deeming J E, Burgan R E, Cohen J D. 1978. The nation fire danger rating system-1978. Washington DC: Forest Service, United States Department of Agriculture.
Fosberg M A, Deeming J E. 1971. Derivation of the 1-and 10-hour timelag fuel moisture calculations for fire-danger rating. USDA Forest Service Research Note RM-207, Fort Collins, CO: Rocky Mountain Forest and Range Experiment Station, Forest Service, United States Department of Agriculture.
Jin S, Chen P Y. 2012. Modelling drying processes of fuelbeds of Scots pine needles with initial moisture content above the fibre saturation point by two-phase models. International Journal of Wildland Fire, 21: 418-427.
Lawson D B, Armitage O B, Hoskins W D. 1996. Diurnal variation on the fine fuel moisture code: tables and computer source code. FRDA Report 245, SSN 0835-752, Victoria, BC: Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre.
Luke R H, McArthur A G. 1978. Bushfires in Australia. Canberra: Australian Government Publishing Service.
Matthews S. 2006a. A process-based model of fine fuel moisture.
International Journal of Wildland Fire, 15: 155-168.
Matthews S, McCaw W L. 2006b. A next-generation fuel moisture model for fire behaviour prediction.
Forest Ecology and Management, 234: S91.
Matthews S, Gould J, McCaw L. 2010. Simple models for predicting dead fuel moisture in eucalyptus forests.
International Journal of Wildland Fire, 19: 459-467.
Murano S L, Russell R N, Lawson B D. 1969. Development of diurnal adjustments table for the fine fuel moisture code. Canadian Forestry Service, Information Report BC-X-35, Columbia: Pacific Forest Research Centre.
Nelson R M. 1984. A method for describing equilibrium moisture content of forest fuels.
Canadian Journal of Forest Research, 14: 597-600.
Nelson R M. 2000. Prediction of diurnal change in 10-h fuel stick moisture content. Canadian Journal of Forest Research, 30: 1071-1087.
Rothermel R C, Wilson R A, Morris G A, et al. 1986. Modeling moisture content of fine dead wildland fuels: input to the behave fire prediction system. USDA Forest Service Research Paper INT-359, Ogden, UT: Intermountain Research Station. Forest Service, United States Department of Agriculture.
Simard A J. 1968. The moisture content of forest fuels. I. A review of the basis concepts. CDFRD Forest Fire Research Institute Information Report FF-X-14, Ottawa, ON: Canadian Department of Forest and Rural Development, Forest Fire Research Institute.
Trevitt A C F. 1988. Weather parameters and fuel moisture content: Standards for fire model inputs. Proceedings of the Conference on Bushfire Modelling and Fire Danger Rating Systems, Canberra, 11-12.

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Models for Predicting the Hourly Fuel Moisture Content on the Forest Floor of Birch Stands in Tahe Forestry Bureau

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